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This paper deals with actuator fault diagnosis of neutral delayed systems with multiple time delays using an unknown input observer. The main purpose is to design an observer that guarantees the asymptotic stability of the estimate error dynamics and the actuator fault detection. The existence conditions for such an observer are established. The main problem studied in this paper aims at designing observer-based fault detection and isolation. The designed observer enhances the robust diagnosis performance, including rapidity and accuracy, and generates residuals that enjoy perfect decoupling properties among faults. Based on Lyapunov stability theory, the design of the observer is formulated in terms of linear matrix inequalities, and the diagnosis scheme is based on a bank of unknown input observers for residual generation that guarantees fault detection and isolation in the presence of external disturbances. A numerical example is presented to illustrate the efficiency of the proposed approach.Key Words: Neutral system with multiple delays, unknown input observer, fault detection and isolation (FDI), linear matrix inequality (LMI).

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Model based supervision of process engineering plants is difficult due to the complexities arising out of the energetic couplings in the model. In this series of two papers, it is shown how the Bond Graph as a multidisciplinary and integrated tool can be used for dynamic modeling and Fault Detection and Isolation heal of process engineering including (energetic and chemical phenomena). In this first paper a pseudo Bond Graph model technique is applied to a pilot plant reactor equipped with a mono-fluid heating/cooling system. A modeling structure has been implemented according to the process sub-units reactor, jacket, supply system and heating/cooling system and validated through experimental observations. In the sequel of this paper, the use of Bond Graph techniques is proposed to indicate the appearance of undesirable product in the reaction mixture, so as to elaborate an efficient and sensitive method for early warning detection of runway. In the second part, the causal and structural proprieties of obtained Bond Graph are used not only to validate the model, but also to provide the computational algorithms to eliminate unknown variables from coupled thermo-chemical models and thus generate Analytical Relations (ARRs) in terms of measurements and parameters for online diagnosis.